Track accepted paper

CiteScore:
6.10ℹCiteScore:2017: 6.100CiteScore measures the average citations received per document published in this title. CiteScore values are based on citation counts in a given year (e.g. 2015) to documents published in three previous calendar years (e.g. 2012 – 14), divided by the number of documents in these three previous years (e.g. 2012 – 14).

Source Normalized Impact per Paper (SNIP):
1.826ℹSource Normalized Impact per Paper (SNIP):2017: 1.826SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.

SCImago Journal Rank (SJR):
0.757ℹSCImago Journal Rank (SJR):2017: 0.757SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.

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Special Issue on Big Data and Smart Cities

Article type name (used in the submission progress): SI: Smart City Big Data

Introduction

A smart city integrates information and communication technologies, as well as Internet of Things (IoT) solutions to reduce costs and resource consumption, enhance performance, and connect and engage more effectively and actively with its citizens. This vast and semi-structured collection of city and citizen-related data provides many opportunities for the development of smart city applications building on big data technologies.

The Smart City Big Data special issue aims to publish work on multidisciplinary research spanning across the of computer science and engineering, environmental studies, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.

Topics for the special issue:

Topics of interest include, but are not limited to:

Big data collection and analysis for smart and connected communities

Urban computing and big data analytics

Social computing big data and networks for smart cities

Urban planning big data evaluation and assessment

Smart city big data governance and management

Data mining and machine learning for smart cities

Smart city transportation big data and analytics

Big data sensing and IoT frameworks and infrastructures

Big data infrastructures and warehouse for smart cities

Smart building big data evaluation

Big data modeling and frameworks for smart cities

Big data security and privacy for smart cities

Big data based city environment monitor, analytics and prediction

Smart city open data

Case Studies and Innovative Applications

In addition to this brief list of possible topics, we will welcome submissions on other topics addressing smart city big data and applications. We will seek papers with conceptual and theoretical contributions and are also open to papers documenting interesting and important effects with a plausible theory to explain these effects in consumer behavior contexts.

Paper Submission Format and Guidelines

All submitted papers must be clearly written in English and must contain only original work, which has not been published by, or is currently under review for, any other journal, conference, symposium, or workshop. Submissions are expected to not exceed 30 pages (including figures, tables, and references) in the journal's single-column format using 11 point font. Detailed submission guidelines are available under "Guide for Authors" at:http://www.journals.elsevier.com/big-data-research/

All manuscripts and any supplementary material should be submitted through the Elsevier Editorial System (EES). The authors must select "SI: Smart City Big Data" as Article Type when they reach the Article Type step in the submission process. The EES website is located at:http://ees.elsevier.com/bdr

All papers will be peer-reviewed by at least three independent reviewers. Requests for additional information should be addressed to the guest editors.